Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges
In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
Machine learning applications in internet-of-drones: Systematic review, recent deployments, and open issues
Deep Learning (DL) and Machine Learning (ML) are effectively utilized in various
complicated challenges in healthcare, industry, and academia. The Internet of Drones (IoD) …
complicated challenges in healthcare, industry, and academia. The Internet of Drones (IoD) …
UAV computing-assisted search and rescue mission framework for disaster and harsh environment mitigation
Disasters are crisis circumstances that put human life in jeopardy. During disasters, public
communication infrastructure is particularly damaged, obstructing Search And Rescue …
communication infrastructure is particularly damaged, obstructing Search And Rescue …
Computing in the sky: A survey on intelligent ubiquitous computing for uav-assisted 6g networks and industry 4.0/5.0
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless …
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless …
Blockchain-based federated learning in UAVs beyond 5G networks: A solution taxonomy and future directions
Recently, unmanned aerial vehicles (UAVs) have gained attention due to increased use-
cases in healthcare, monitoring, surveillance, and logistics operations. UAVs mainly …
cases in healthcare, monitoring, surveillance, and logistics operations. UAVs mainly …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Iot malware analysis using federated learning: A comprehensive survey
The Internet of Things (IoT) has paved the way to a highly connected society where all things
are interconnected and exchanging information has become more accessible through the …
are interconnected and exchanging information has become more accessible through the …
A survey on decentralized federated learning
In recent years, federated learning (FL) has become a very popular paradigm for training
distributed, large-scale, and privacy-preserving machine learning (ML) systems. In contrast …
distributed, large-scale, and privacy-preserving machine learning (ML) systems. In contrast …
Federated learning in satellite constellations
Empowered by their exceptional versatility and autonomy, unmanned vehicles (UxVs),
including ground, aerial, surface and underwater vehicles, are emerging as promising tools …
including ground, aerial, surface and underwater vehicles, are emerging as promising tools …